code: def collate_task(self, task):
      if isinstance(task, TorchDataset):
          return self.collate_fn(
              [task[idx] for idx in range(len(task))]
          )
      elif isinstance(task, OrderedDict):
          return OrderedDict(
              [
                  (key, self.collate_task(subtask))
                  for (key, subtask) in task.items()
              ]
          )
      else:
          raise NotImplementedError()
  
file_path: pytorch-meta/torchmeta/utils/data/dataloader.py
imports: from collections import OrderedDict
  from torch.utils.data import DataLoader
  from torch.utils.data.dataloader import default_collate
  from torch.utils.data.dataset import Dataset
  from torchmeta.utils.data.dataset import CombinationMetaDataset
  from torchmeta.utils.data.sampler import CombinationSequentialSampler, CombinationRandomSampler
label_desc: Use image node_id 2 for calling the BatchMetaCollate obj's underlying member method code with example usage: obj.collate_task(task) and returns: self, OrderedDict